Title: World Wide Web Image Search Engines
Author: Stan Sclaroff
Date: 27 May 1995
Abstract:
We propose the development of a world wide web image search engine
that crawls the web collecting information about the images it finds,
computes the appropriate image decompositions and indices, and stores
this extracted information for searches based on image content.
Indexing and searching images need not require solving the image
understanding problem. Instead, the general approach should be to
provide an arsenal of image decompositions and discriminants that can
be precomputed for images. At search time, users can select a
weighted subset of these decompositions to be used for computing image
similarity measurements. While this approach avoids the
search-time-dependent problem of labeling what is important in images,
it still holds several important problems that require further
research in the area of query by image content. We briefly explore
some of these problems as they pertain to shape.
(white paper presented at the NSF Workshop on Visual Information
Management, MIT, June 1995)